With the progress of all-Internet Protocol (IP) networks, a wealth of services bring both opportunities and challenges to an operator. Service traffic grows explosively. To better run a network and provide users with better experience, it is needed to analyze Internet users' access behavior, and thereby learn users' interests, network-wide application statuses and application trends, and so on, so as to better provide personalized services for the users and optimize the network.
User behavior analysis (UBA) can be used not only for fine operation planning and network planning, but also for services such as precise advertisement push, and an operator may accordingly run high-value value-added services (such as an advertisement pushing service). According to statistics, turnover of international Internet advertising in 2007 is 44 billion U.S. dollars (with a growth rate exceeding 44% for three consecutive years), where China accounts for 10.3 billion Chinese Yuan, and it is expected to reach 70.3 billion Chinese Yuan in 2012.
Common existing architectures for UBA device deployment are shown in FIGS. 1A and 1B, where different UBA devices may be deployed in different areas. A UBA device needs to analyze content accessed by users. Generally, daily amount of user-accessed content is huge, and the amount of contents added to the network each day may also be large. It is found by practice that UBA devices in the existing architectures have limited analysis capabilities, and a problem of repeated analysis between different UBA devices often occurs, which further affects performance efficiency.